Datasets
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Code /
Hugging Face /
Text-to-Image GenAI /
Stable Diffusion text-to-image kkawchak.ipynb
6937 lines (6937 with data), 249.7 kB
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"cells": [
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"id": "2lLlNjwVDupR"
},
"outputs": [],
"source": [
"# !pip install diffusers\n",
"# !pip install accelerate"
]
},
{
"cell_type": "code",
"source": [
"# doctor helping another patient"
],
"metadata": {
"id": "_GKGxe1JPTlj"
},
"execution_count": null,
"outputs": []
},
{
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"from diffusers import StableDiffusionPipeline\n",
"import torch\n",
"\n",
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
"pipe = pipe.to(\"cuda\")\n",
"\n",
"prompt = \"doctor helping another patient\"\n",
"image = pipe(prompt).images[0]\n",
"\n",
"image.save(\"doctor helping another patient_1.png\")"
],
"metadata": {
"colab": {
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"height": 81,
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{
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"data": {
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"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
],
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{
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"import torch\n",
"\n",
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
"pipe = pipe.to(\"cuda\")\n",
"\n",
"prompt = \"doctor helping another patient\"\n",
"image = pipe(prompt).images[0]\n",
"\n",
"image.save(\"doctor helping another patient_2.png\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 81,
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"id": "bq_USd4DMPSi",
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{
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"data": {
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"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
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{
"cell_type": "code",
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"from diffusers import StableDiffusionPipeline\n",
"import torch\n",
"\n",
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
"pipe = pipe.to(\"cuda\")\n",
"\n",
"prompt = \"doctor helping another patient\"\n",
"image = pipe(prompt).images[0]\n",
"\n",
"image.save(\"doctor helping another patient_3.png\")"
],
"metadata": {
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},
"id": "KqvhVcicMP-A",
"outputId": "cb2876d0-fab0-4f6b-b426-bd0bd672ec15"
},
"execution_count": 8,
"outputs": [
{
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"data": {
"text/plain": [
"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
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{
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},
{
"cell_type": "code",
"source": [
"# nurses utilizing medical ai at the hospital"
],
"metadata": {
"id": "0YVlizsgMQ07"
},
"execution_count": 8,
"outputs": []
},
{
"cell_type": "code",
"source": [
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"import torch\n",
"\n",
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
"pipe = pipe.to(\"cuda\")\n",
"\n",
"prompt = \"nurses utilizing medical ai at the hospital\"\n",
"image = pipe(prompt).images[0]\n",
"\n",
"image.save(\"nurses utilizing medical ai at the hospital_1.png\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 81,
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"execution_count": 13,
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{
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"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
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{
"cell_type": "code",
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"import torch\n",
"\n",
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
"pipe = pipe.to(\"cuda\")\n",
"\n",
"prompt = \"nurses utilizing medical ai at the hospital\"\n",
"image = pipe(prompt).images[0]\n",
"\n",
"image.save(\"nurses utilizing medical ai at the hospital_2.png\")"
],
"metadata": {
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"height": 81,
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"id": "3-eyMmFFMRca",
"outputId": "5c77163c-7fbb-4f20-ac8f-b1c6a6e1ff00"
},
"execution_count": 14,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "2e56f2996b7a4d8e9240dac6c23e6bf7"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
" 0%| | 0/50 [00:00<?, ?it/s]"
],
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"version_major": 2,
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}
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]
},
{
"cell_type": "code",
"source": [
"from diffusers import StableDiffusionPipeline\n",
"import torch\n",
"\n",
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
"pipe = pipe.to(\"cuda\")\n",
"\n",
"prompt = \"nurses utilizing medical ai at the hospital\"\n",
"image = pipe(prompt).images[0]\n",
"\n",
"image.save(\"nurses utilizing medical ai at the hospital_3.png\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 81,
"referenced_widgets": [
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]
},
"id": "WEXG6koVMRmh",
"outputId": "65af5478-2f83-4f5d-f1e7-1c00fc6ad194"
},
"execution_count": 15,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "27493f54a44d4d9cad9ef751cbc1e3ba"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
" 0%| | 0/50 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "6d98c2f3a30c42b58ff98dfb2688ac90"
}
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"# hospital staff using generative ai in safe and effective ways"
],
"metadata": {
"id": "IjNrgMG6MRws"
},
"execution_count": 15,
"outputs": []
},
{
"cell_type": "code",
"source": [
"from diffusers import StableDiffusionPipeline\n",
"import torch\n",
"\n",
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
"pipe = pipe.to(\"cuda\")\n",
"\n",
"prompt = \"hospital staff using generative ai in safe and effective ways\"\n",
"image = pipe(prompt).images[0]\n",
"\n",
"image.save(\"hospital staff using generative ai in safe and effective ways_1.png\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 81,
"referenced_widgets": [
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},
"id": "wf0GrEZgMR7U",
"outputId": "e8d3a307-32cb-4fb2-dc17-6a8d8a70c57b"
},
"execution_count": 18,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "f6c2033b634349d49b372566664928d5"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
" 0%| | 0/50 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "0d3d53d9c1be4465a485f704215a6f92"
}
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"from diffusers import StableDiffusionPipeline\n",
"import torch\n",
"\n",
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
"pipe = pipe.to(\"cuda\")\n",
"\n",
"prompt = \"hospital staff using generative ai in safe and effective ways\"\n",
"image = pipe(prompt).images[0]\n",
"\n",
"image.save(\"hospital staff using generative ai in safe and effective ways_2.png\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 81,
"referenced_widgets": [
"e47bc7d5085649ff8792ae1b9712355b",
"ed411faa1c59493987965ea3633f3ff4",
"2d601149267e4acdb31587f054d35101",
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"97794969185b46d0b9b9e8408bf1b3ad",
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]
},
"id": "mD2PK7urMSFf",
"outputId": "36560b2a-7c63-4187-c202-b33dcd4cbca6"
},
"execution_count": 19,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "e47bc7d5085649ff8792ae1b9712355b"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
" 0%| | 0/50 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "aadf05d217984873a70334a8856cc665"
}
},
"metadata": {}
}
]
},
{
"cell_type": "code",
"source": [
"from diffusers import StableDiffusionPipeline\n",
"import torch\n",
"\n",
"model_id = \"runwayml/stable-diffusion-v1-5\"\n",
"pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)\n",
"pipe = pipe.to(\"cuda\")\n",
"\n",
"prompt = \"hospital staff using generative ai in safe and effective ways\"\n",
"image = pipe(prompt).images[0]\n",
"\n",
"image.save(\"hospital staff using generative ai in safe and effective ways_3.png\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 81,
"referenced_widgets": [
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"923ee0b1db09476a9efe37096daf67c1",
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]
},
"id": "-W49D-VeMSPn",
"outputId": "d685aec0-ba5f-4c07-e6ac-96af79c256e1"
},
"execution_count": 20,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"Loading pipeline components...: 0%| | 0/7 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "b979e2c8706547eb90b03be9ec46c0fc"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
" 0%| | 0/50 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "6bb49ef38c354b49a43d78921d44f121"
}
},
"metadata": {}
}
]
}
]
}